ArticleExperimental and therapeutic medicine2018
Investigation of the values of CT perfusion imaging and ultrasound elastography in the diagnosis of liver fibrosis.
Article in Experimental and therapeutic medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed, 6 citations in OpenAlex.
- Noninvasive Tests (NITs) for Hepatic Fibrosis in Fatty Liver Syndrome.Life (Basel, Switzerland) · 2020Review
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3 authors at 2 institutions in 1 country.
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Abstract
This study intended to investigate the clinical application values of computed tomography (CT) perfusion imaging and ultrasound elastography in the diagnosis of liver fibrosis, and to analyze the characteristics and diagnostic values of the two methods in liver fibrosis. A total of 320 patients diagnosed with suspected liver fibrosis in Qingdao Municipal Hospital from April 2014 to May 2016 were selected. The patients were diagnosed by ultrasound elastography and CT perfusion imaging, respectively, and the influencing characteristics and diagnostic accuracies of the two methods were compared. Among 320 patients, there were 315 definitely diagnosed with liver fibrosis through liver biopsy. The accuracy of CT perfusion imaging was 95.63% (306/325), while that of ultrasound elastography was 91.88% (294/320); there was a significant difference in accuracy between the two methods (P>0.05). CT perfusion imaging was superior to ultrasound elastography in the degree of liver fibrosis (P<0.05). Receiver operating characteristic (ROC) curve analysis showed that the areas under the curve (AUC) of patients were 0.841 and 0.865 in S1 (P>0.05), 0.830 and 0.887 in S2 (P>0.05), 0.851 and 0.931 in S3 (P>0.05), and 0.951 and 0.970 in S4, respectively (P>0.05). AUC values of ROC curves of CT perfusion imaging and ultrasound elastography in diagnosing liver fibrosis were 0.833 and 0.857, respectively (P>0.05). Both CT perfusion imaging and ultrasound elastography have relatively high accuracies in the clinical diagnosis of liver fibrosis, and they are worth promoting and applying. However, the best imaging method needs to be selected according to the actual situation of patients and research purpose.
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